Neighbour search (NS) is the core of any implementations of smoothed particle hydrodynamics (SPH). In this paper, we present an efficient $\mathcal{O}(N\log N)$ neighbour search method based on the plane sweep (PW) algorithm with $N$ being the number of SPH particles. The resulting method, dubbed the PWNS method, is totally independent of grids (i.e., purely meshfree) and capable of treating variable smoothing length, arbitrary particle distribution and heterogenous kernels. Several state-of-the-art data structures and algorithms, e.g., the segment tree and the Morton code, are optimized and implemented. By simply allowing multiple lines to sweep the SPH particles simultaneously from different initial positions, a parallelization of the PWNS method with satisfactory speedup and load-balancing can be easily achieved. That is, the PWNS SPH solver has a great potential for large scale fluid dynamics simulations.
The generalization of learning offers a unique window for investigating the nature of motor learning. Error-based motor learning reportedly cannot generalize to distant directions because the aftereffects are direction specific. This direction specificity is often regarded as evidence that motor adaptation is model-based learning, and is constrained by neuronal tuning characteristics in the primary motor cortices and the cerebellum. However, recent evidence indicates that motor adaptation also involves model-free learning and explicit strategy learning. Using rotation paradigms, here we demonstrate that savings (faster relearning), which is closely related to model-free learning and explicit strategy learning, is also direction specific. However, this new direction specificity can be abolished when the participants receive exposure to the generalization directions via an irrelevant visuomotor gain-learning task. Control evidence indicates that this exposure effect is weakened when direction error signals are absent during gain learning. Therefore, the direction specificity in visuomotor learning is not solely related to model-based learning; it may also result from the impeded expression of model-free learning and explicit strategy learning with untrained directions. Our findings provide new insights into the mechanisms underlying motor learning, and may have important implications for practical applications such as motor rehabilitation. SIGNIFICANCE STATEMENT: Motor learning is more useful if it generalizes to untrained scenarios when needed, especially for sports training and motor rehabilitation. However, as a form of motor learning, motor adaptation is typically direction specific. Here we first show that savings with motor adaptation, an index for model-free learning and explicit strategy learning in motor learning, is also direction specific. However, the participants' additional exposure to untrained directions via an irrelevant gain-learning task can enable the complete generalization of learning. Our findings challenge existing models of motor generalization and may have important implications for practical applications.
Box C (RUGAUGA)/D (CUGA) and H (ANANNA)/ACA small nucleolar RNAs (snoRNAs) are important for the modification and processing of rRNA during ribosome biogenesis in eukaryotes. However, the molecular role of snoRNAs throughout the multiple steps of pre-rRNA processing remains poorly understood. This study shows that an uncharacterized C/D box snoRNA, HIDDEN TREASURE 2 (HID2), functions as a prominent player in the monitoring of efficient pre-rRNA processing, which, in turn, is essential for accurate ribosome assembly in Arabidopsis. Our data explore a link between a spatially regulated snoRNA and the complexity and the precise control of ribosome biogenesis. Further, the conservation of HID2’s signature motif and function highlights its importance in multicellular organisms. hid2 appears to be a representative snoRNA mutant exhibiting pleiotropic developmental defects in plants.Ribosome production in eukaryotes requires the complex and precise coordination of several hundred assembly factors, including many small nucleolar RNAs (snoRNAs). However, at present, the distinct role of key snoRNAs in ribosome biogenesis remains poorly understood in higher plants. Here we report that a previously uncharacterized C (RUGAUGA)/D (CUGA) type snoRNA, HIDDEN TREASURE 2 (HID2), acts as an important regulator of ribosome biogenesis through a snoRNA–rRNA interaction. Nucleolus-localized HID2 is actively expressed in Arabidopsis proliferative tissues, whereas defects in HID2 cause a series of developmental defects reminiscent of ribosomal protein mutants. HID2 associates with the precursor 45S rRNA and promotes the efficiency and accuracy of pre-rRNA processing. Intriguingly, disrupting HID2 in Arabidopsis appears to impair the integrity of 27SB, a key pre-rRNA intermediate that generates 25S and 5.8S rRNA and is known to be vital for the synthesis of the 60S large ribosomal subunit and also produces an imbalanced ribosome profile. Finally, we demonstrate that the antisense-box of HID2 is both functionally essential and highly conserved in eukaryotes. Overall, our study reveals the vital and possibly conserved role of a snoRNA in monitoring the efficiency of pre-rRNA processing during ribosome biogenesis.
Hydrogen cyanide (HCN) is considered a marker for biomass burning emissions and is a component of vehicle exhaust. Despite its potential health impacts, vehicular HCN emissions estimates and their contribution to regional budgets are highly uncertain. In the current study, Proton Transfer Reaction Time of Flight-Mass Spectrometry (PTR-ToF-MS) was used to measure HCN emission factors from the exhaust of individual diesel, biodiesel and gasoline vehicles. Laboratory emissions data as a function of fuel type and driving mode were combined with ambient measurement data and model predictions. The results indicate that gasoline vehicles have the highest emissions of HCN (relative to diesel fuel) and that biodiesel fuel has the potential to significantly reduce HCN emissions even at realistic 5% blend levels. The data further demonstrate that gasoline direct injection (GDI) engines emit more HCN than their port fuel injection (PFI) counterparts, suggesting that the expected full transition of vehicle fleets to GDI will increase HCN emissions. Ambient measurements of HCN in a traffic dominated area of Toronto, Canada were strongly correlated to vehicle emission markers and consistent with regional air quality model predictions of ambient air HCN, indicating that vehicle emissions of HCN are the dominant source of exposure in urban areas. The results further indicate that additional work is required to quantify HCN emissions from the modern vehicle fleet, particularly in light of continuously changing engine, fuel and after-treatment technologies. Crown Copyright (C) 2016 Published by Elsevier Ltd.